• Journal of the Society of Disaster Information
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• v.19 no.3
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• pp.582-596
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• 2023

Purpose: This study aims to explore the ways to improve the security of temporary shelters in case of nuclear power plant accidents. Method: In this study, we mainly rely on the case studies on previous nuclear power plant accidents-Chernobyl, Fukushima, and Three Mile Island (TMI) cases. Result: The current radiation emergency response plans for nuclear power plant accidents center around the evacuation procedure. As a result, the concept of "shelter in place" has been understood as a means of assisting resident evacuation. However, based on the case studies, we find that encouraging shelter in place, rather than simply emphasizing evacuation, would help minimize unnecessary casualties, especially in case of the accidents rated greater than or equal to INES 5. To facilitate better shelter in place, we recommend utilize apartments as temporary shelters and suggest some possible improvements to ensure those apartments could be equipped with technologies for high radiation protection. Conclusion: To ensure better shelter in place, we recommend using apartments as temporary shelters, and we seek to supplement the function of apartments by using shielding, positive pressure, and sealing technologies.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.3
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• pp.33-40
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• 2010

Recently Yoon et al. proposed the remote user authentication scheme using smart cards. But their scheme has not satisfied security requirements which should be considered in the user authentication scheme using the password based smart card. In this paper, we prove that Yoon et al.'s scheme is vulnerable to a password guessing attack in case that the attacker steals the user's smart card and extracts the information from the smart card. Accordingly, we propose the improved user authentication scheme based on the hash function and random nonce that can withstand various possible attacks including a password guessing attack. The result of comparative analysis demonstrates that the our proposed scheme is much more secure and efficient than the Yoon et al.'s scheme, with a trivial trade-off to require just a few more exclusive-OR operations.

• Ocean and Polar Research
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• v.45 no.2
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• pp.71-87
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• 2023

Climate change causes ocean warming, ocean acidification, sea-level rise, dynamic coastal risk, change of ecosystem structure and function, and degradation of ecosystem services. Not only that, but it has negatively impacted the well-being of people, society, and culture, including food security, water resources, water quality, livelihood, health, welfare, infrastructure, transport, tourism, recreation, and so on, especially by particularly degrading indigenous communities and generating an inequitable distribution of benefits and costs. As pointed out here, these adverse impacts of climate change on the ocean have been emphasized at the international and national levels. In contrast, the ocean field has been neglected in the climate change conversation for too long. However, since the UNFCCC COP 25, the ocean has been drawn into the discussion as a solution to address climate change. Moreover, the U.S. Congress recently unveiled a bill called the 'Ocean-Based Climate Solution Act, OBCSA' that reflects the new paradigm of the international regime. The comprehensive legislative bill includes elements related to climate inequity, a blue economy, and a community-led bottom-up policy mechanism, which will have a significant bearing on the ocean-climate legal system. Therefore, this study reviews the OBCSA and deduces implications with regard to the ocean-climate legal system in Korea.

• Journal of Korean Neurosurgical Society
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• v.66 no.5
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• pp.488-493
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• 2023

We aimed to develop a cloud-based telemedicine platform for patients with intracerebral hemorrhage (ICH) at local hospitals in rural and underserved areas in Gangwon-do using artificial intelligence and non-face-to-face collaboration treatment technology. This is a prospective and multi-center development project in which neurosurgeons from four university hospitals in Gangwon-do will participate. Information technology experts will verify and improve the performance of the cloud-based telemedicine collaboration platform while treating ICH patients in the actual medical field. Problems identified will be resolved, and the function, performance, security, and safety of the telemedicine platform will be checked through an accredited certification authority. The project will be carried out over 4 years and consists of two phases. The first phase will be from April 2022 to December 2023, and the second phase will be from April 2024 to December 2025. The platform will be developed by dividing the work of the neurosurgeons and information technology experts by setting the order of items through mutual feedback. This article provides information on a project to develop a cloud-based telemedicine platform for acute ICH patients in Gangwon-do.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.279-282
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• 2022

Acute lymphoblastic leukemia is an acute leukemia caused by suppression of bone marrow function due to overgrowth of immature lymphocytes in the bone marrow. It accounts for 30% of acute leukemia in adults, and children show a cure rate of over 80% with chemotherapy, while adults show a low survival rate of 20% to 50%. However, research on a machine learning algorithm based on medical image data for the diagnosis of acute lymphoblastic leukemia is in the initial stage. In this paper, we compare and analyze CNN algorithm models for quick and accurate diagnosis. Using four models, an experimental environment for comparative analysis of acute lymphoblastic leukemia diagnostic models was established, and the algorithm with the best accuracy was selected for the given medical image data. According to the experimental results, among the four CNN models, the InceptionV3 model showed the best performance with an accuracy of 98.9%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.184-186
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• 2022

Recently, as interest in personal information protection has increased, various apps for personal information protection have emerged. These apps protect data in various formats, such as photos, videos, and documents containing personal information, using encryption and hide functions. These apps can have a positive effect on personal information protection, but in digital forensics, they act as anti-forensic because they can be difficult to analyze data during the investigation process. In this paper, finds out PIN, an access control function, through reverse engineering on Calculator - photo vault, one of the personal information protection apps, and files such as photos and documents to which encryption and hide were applied. In addition, the vulnerability to this app was analyzed by research decryption for database files where logs for encrypted and hide files are stored.

• KNOM Review
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• v.22 no.3
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• pp.1-12
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• 2019

Recently, researching using big data and AI has emerged as a major issue in the ICT field. But, the size of big data for research is growing exponentially. In addition, users of data transmission of existing network method suggest that the problem the time taken to send and receive big data is slower than the time to copy and send the hard disk. Accordingly, researchers require dynamic and flexible network technology that can transmit data at high speed and accommodate various network structures. SDN/NFV technologies can be programming a network to provide a network suitable for the needs of users. It can easily solve the network's flexibility and security problems. Also, the problem with performing AI is that centralized data processing cannot guarantee real-time, and network delay occur when traffic increases. In order to solve this problem, the edge-computing technology, should be used which has moved away from the centralized method. In this paper, we investigate the concept and research trend of SDN, NFV, and edge-computing technologies, and analyze the trends of data central network technologies used by combining these three technologies.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.159-166
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• 2009

A nature immunity system responds sensitively to an external invasion with various functions in a lot of bodies, besides it there is a function to remember information to have been currently infected. we propose a hybrid model similar to immune system which combine with the antibody which applied genetic algorithm as select antibody and the arbitrary abnormal system call sequence that applied negative selection of a nature immunity system. A proposed model uses an arbitrary abnormal system Kol sequence in order to reduce a positive defect and a negative defect. Data used to experiment are send mail data processed UNM (University of New Maxico). The negative defect that an experiment results proposal model judged system call more abnormal than the existing negative selection to normal system call appeared 0.55% low.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.5
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• pp.19-28
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• 2017

Various methods for reducing the load on the server have been implemented in performing face recognition remotely by the spread of IP security cameras. In this paper, IP surveillance cameras at remote sites are input through a DSP board equipped with face detection function, and then face detection is performed. Then, the facial region image is transmitted to the server, and the face recognition processing is performed through face recognition distributed processing. As a result, the overall server system load and significantly reduce processing and real-time face recognition has the advantage that you can perform while linked up to 256 cameras. The technology that can accomplish this is to perform 64-channel face recognition per server using distributed processing server technology and to process face search results through 250 camera channels when operating four distributed processing servers there was.

• Smart Structures and Systems
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• v.31 no.1
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• pp.57-68
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• 2023

Bridge hangers, such as those in suspension and cable-stayed bridges, suffer from cumulative fatigue damage caused by dynamic loads (e.g., cyclic traffic and wind loads) in their service condition. Thus, the identification of damage to hangers is important in preserving the service life of the bridge structure. This study develops a new method for condition assessment of bridge hangers. The tension force of the bridge and the damages in the element level can be identified using the Bayesian optimization method. To improve the number of observed data, the additional mass method is combined the Bayesian optimization method. Numerical studies are presented to verify the accuracy and efficiency of the proposed method. The influence of different acquisition functions, which include expected improvement (EI), probability-of-improvement (PI), lower confidence bound (LCB), and expected improvement per second (EIPC), on the identification of damage to the bridge hanger is studied. Results show that the errors identified by the EI acquisition function are smaller than those identified by the other acquisition functions. The identification of the damage to the bridge hanger with various types of boundary conditions and different levels of measurement noise are also studied. Results show that both the severity of the damage and the tension force can be identified via the proposed method, thereby verifying the robustness of the proposed method. Compared to the genetic algorithm (GA), particle swarm optimization (PSO), and nonlinear least-square method (NLS), the Bayesian optimization (BO) performs best in identifying the structural damage and tension force.